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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Future Grid State Modeling for Transactive Systems

The simulation design and evaluation of a transactive energy system is contingent on the setting in which it would exist, which could vary significantly with the many drivers that impact the potential future states of the power system. This report summarizes the development of the Transactive Future Grid State (TFGS) model, which is a lightweight capacity expansion model that will support transactive energy research by allowing users to explore alternative future states. The TFGS model determines the long-term generation capacity needs of a given power system that satisfy specified constraints and support a least cost hourly dispatch. This is accomplished by solving a single optimization problem that simultaneously finds the generation fleet with capacity sufficient to meet peak load and the flexibility to meet hourly operational dispatch, all at lowest cost. The TFGS model was applied to a larger ongoing study taking place that will be simulating how distribution system operators (DSOs) could use a transactive energy system to manage distributed energy resources. The larger study, commonly referred to as the DSO+T study, involves two parallel analyses; one that represents the system today and one that represents a future system with a high degree of renewable energy penetration. The TFGS model provided the generation mix of the high renewable base case. As the TFGS model was being used to provide inputs to the DSO+T study, two issues became apparent. First, additional functionality would have been useful, and second, a larger-than-anticipated amount of user inputs and data were required to successfully use the TFGS model. These discoveries have lead to the recommendation of specific functionality that can be added in future development of the tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

SU-E-T-36: A GPU-Accelerated Monte-Carlo Dose Calculation Platform and Its Application Toward Validating a ViewRay Beam Model

Purpose: To build a fast, accurate and easily-deployable research platform for Monte-Carlo dose calculations. We port the dose calculation engine PENELOPE to C++, and accelerate calculations using GPU acceleration. Simulations of a Co-60 beam model provided by ViewRay demonstrate the capabilities of the platform. Methods: We built software that incorporates a beam model interface, CT-phantom model, GPU-accelerated PENELOPE engine, and GUI front-end. We rewrote the PENELOPE kernel in C++ (from Fortran) and accelerated the code on a GPU. We seamlessly integrated a Co-60 beam model (obtained from ViewRay) into our platform. Simulations of various field sizes and SSDs using a homogeneous water phantom generated PDDs, dose profiles, and output factors that were compared to experiment data. Results: With GPU acceleration using a dated graphics card (Nvidia Tesla C2050), a highly accurate simulation – including 100*100*100 grid, 3×3×3 mm3 voxels, <1% uncertainty, and 4.2×4.2 cm2 field size – runs 24 times faster (20 minutes versus 8 hours) than when parallelizing on 8 threads across a new CPU (Intel i7-4770). Simulated PDDs, profiles and output ratios for the commercial system agree well with experiment data measured using radiographic film or ionization chamber. Based on our analysis, this beam model is precise enough for general applications. Conclusions: Using a beam model for a Co-60 system provided by ViewRay, we evaluate a dose calculation platform that we developed. Comparison to measurements demonstrates the promise of our software for use as a research platform for dose calculations, with applications including quality assurance and treatment plan verification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

DISTINCT: Diversity in Solar Talent Through INnovative Curriculum and Training: An Integrated Research and Education Approach towards Creating Diversity and Advancing Utility-Scale Solar Technology

The DISTINCT project research objective is to develop an innovative N-port power converter for a utility-scale PV system that is modular, compact and cost-effective and that will enable the integration of a high-frequency, high-voltage solid-state transformer. The novelty of the proposed research is the electrical power conversion architecture using an N-port converter system that replaces the output 60Hz transformer with an integrated high-frequency low-weight solid-state transformer reducing power electronics and BOS costs to meet SunShot goals through modularity and direct high-voltage interconnection. A challenge in direct integration with a 13.8kV line is the high voltage handling capacity of the converters combined with high efficiency operation. The front-end converter for each port is a Neutral-Point Clamped (NPC) Multi-Level dc-dc Dual-Active Bridge (ML-DAB) which allows Maximum Power Point Tracking (MPPT). The integrated high frequency transformer provides the galvanic isolation between the PV and grid side and also steps up the low dc voltage from PV source. Following the ML-DAB stage, in each port, is an inverter with H-bridge configuration or NPC configuration. N number of NPC inverters’ outputs are cascaded to attain the per-phase line-to-neutral voltage to connect directly to the distribution grid (i.e. 13.8 kV). The cascaded inverters have the inherent advantage of using lower rated devices, smaller filters and low Total Harmonic Distortion (THD) required for PV grid interconnection. Our analysis and simulation results show improved performance on cost, efficiency, service life with zero downtime and THD. A comprehensive control scheme is presented to ensure the maximum power from each port and each phase are sent to the grid. A functional prototype of a 2-port converter with ML-DAB and cascaded H-bridges has been designed, built, and tested in a laboratory setup to verify the target technical metrics. The N-port converter system due to its modular structure with individual control per port can be easily adapted to integrate functionalities that go well beyond the conventional grid support functions and mitigates impacts of forecasted fast ramp downs or ramp ups and single-fault conditions by automatic reconfiguration of the output.

14 SOLAR ENERGY↗
DOE OSTI2025

Convective shells in the interior of Cepheid variable stars: Overshooting models based on hydrodynamic simulations

Context. Because Cepheid variable stars have long been used as a cosmic benchmark for scaling distances in our Galaxy and beyond, the accuracy of stellar evolution models for Cepheids have wide-reaching effects. However, our understanding of the dynamics in the interiors of these physically complex stars is limited. Aims. Our goal is to provide a detailed multi-dimensional picture of hydrodynamic convection and convective boundary mixing in the interior of Cepheids. Methods. Using the Modules for Experiments in Stellar Astrophysics (MESA), we studied the structure of intermediate-mass stars that cross the instability strip. Then, we performed two-dimensional hydrodynamic simulations of six stars with the fully compressible Multidimensional Stellar Implicit Code (MUSIC). Our simulations did not model the radial pulsations but focused on the interior structure of this family of stars. We developed and applied a new statistical analysis to examine convection and convective boundary mixing in the interior of these stellar simulations. Results. Based on a grid of MESA models, we demonstrated that a common structure for intermediate mass Cepheids includes an interior convective shell as well as a thin outer convective envelope. Using the extreme value theory approach to analyze our MUSIC simulation data, we found that overshooting above the convective shell fills the space between these convectively unstable layers. We developed a new statistical analysis that provides a clearer picture of how overshooting fills this layer; it also allowed us to formulate a detailed comparison between overshooting above and below the convective shell. Our analysis effectively decomposes the overshooting layer into two layers: a weak overshooting layer and a strong overshooting layer. Statistically, this is accomplished by decomposing the strongly non-Gaussian probability density function into a mixture of gamma distributions. Using our mixture model, we showed that the ratio of overshooting lengths above and below the convective shell depends directly on the radial extent of the convective shell as well as its depth in the star. We proposed a new form for the diffusion coefficient that addresses the need for overlapping overshooting layers between convective shells. We introduced the idea of a “super-mixing layer” where overshooting from both the convective shell and the convective envelope results in efficient mixing and could be viewed as merging the two adjacent convective zones.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

CEEP (Cyber-Energy Emulation Platform) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Vaughan, Evan↗
DOE OSTI2022

Cyber Energy Emulation Platform (CEEP) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Rivera, Joshua↗
DOE OSTI2015

Simulator of galaxy millimeter/submillimeter emission (SÍGAME): The [C ii]–SFR relationship of massive z = 2 main sequence galaxies

We present SÍGAME simulations of the [C II] 157.7 μm fine structure line emission from cosmological smoothed particle hydrodynamics simulations of seven main sequence galaxies at z = 2. Using sub-grid physics prescriptions the gas in our simulations is modeled as a multi-phased interstellar medium comprised of molecular gas residing in giant molecular clouds, an atomic gas phase associated with photo-dissociation regions (PDRs) at the cloud surfaces, and a diffuse, ionized gas phase. Adopting logotropic cloud density profiles and accounting for heating by the local FUV radiation field and cosmic rays by scaling both with local star formation rate (SFR) volume density, we calculate the [C II] emission using a photon escape probability formalism. The [C II] emission peaks in the central ≲1 kpc of our galaxies as do the SFR radial profiles, with most [C II] (≳70%) originating in the molecular gas phase, whereas further out (≳2 kpc), the atomic/PDR gas dominates (≳90%) the [C II] emission, no longer tracing ongoing star formation. Throughout, the ionized gas contribution is negligible (≲3%). The [C II] luminosity versus SFR ([C II]–SFR) relationship, integrated as well as spatially resolved (on scales of 1 kpc), delineated by our simulated galaxies is in good agreement with the corresponding relations observed locally and at high redshifts. In our simulations, the molecular gas dominates the [C II] budget at SFR≳20 M{sub ⊙} yr{sup −1} (Σ{sub SFR} ≳0.5 M{sub ⊙} yr{sup −1} kpc{sup −2}), while atomic/PDR gas takes over at lower SFRs, suggesting a picture in which [C II] predominantly traces the molecular gas in high-density/pressure regions where star formation is ongoing, and otherwise reveals the atomic/PDR gas phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments

We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermal and electric multidomain dynamic model for integration of power grid distribution with behind-the-meter devices

As renewable energy sources like solar and wind power become more integrated into the grid, coordinated control of behind-the-meter devices is crucial for enhancing grid flexibility and reliability and for meeting cost targets, with standardized models being developed to support this transition. The increasing flexibility and uncertainty of integrated renewable energy grids, along with interactions between various subsystems, make traditional steady-state modeling insufficient to capture transient and dynamic behaviors. Current models (e.g., composite load and battery equivalent models) focus on thermodynamic or electrical characteristics but overlook critical electromechanical interactions. This limits the ability to share performance information for grid services and hampers fast dynamic simulations. In addition, motor stalling is usually triggered by a fault event and attributed to the characteristics of the mechanical torque of the motor, resulting in absorption of a large amount of reactive power during the stalling period. Further, this significant withdrawal of reactive power will deteriorate the dynamic voltage stability of power grids and cause delayed voltage recovery. Therefore, an in-depth modeling of the thermodynamics or mechanical torque is essential to study the impacts of the realistic torque characteristics of those behind-the-meter devices on power system voltage stability. This study developed a dynamic multidomain model for building HVAC systems, such as air-source heat pumps, to simulate their thermal and electrical responses to grid transients. The model can accurately predict power metrics with a mean absolute percentage error of 10%, by validating against with power system computer-aided design performance data. Case studies demonstrate the model capability of capturing the transient response to sudden voltage changes, rapid load fluctuations, and system shutdowns respectively. During a sudden voltage drop (30% for 0.1s), a fully loaded heat pump’s motor speed dropped, continued declining, and shut down after 3.6s, with severe power oscillations and a torque spike. A partially loaded unit experienced temporary oscillations but stabilized. Under higher building loads, compressor speed increased from 64% to 100%, with power and torque rising before stabilizing. In safety-triggered shutdowns, power decreased after minor fluctuations, and torque briefly spiked before dropping to zero.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Smoothed boundary method for simulating incompressible flow in complex geometries

Simulating flow through porous media with explicit considerations of complex microstructures is very challenging using conventional sharp-interface methods because of the difficulties in generating meshes conformal to complex geometries. In this work, a diffuse interface embedded boundary method known as the Smoothed Boundary Method (SBM) is utilized to facilitate simulations of fluid dynamics involving complex geometries. In diffuse-interface methods, the geometry is described by a domain parameter. The SBM allows the straightforward reformulation of the time-dependent Navier-Stokes equations in terms of this domain parameter, using only algebraic identities. Thus, enforcing the appropriate boundary conditions at the irregular embedded boundary is greatly simplified. Adaptive mesh refinement is used to increase the accuracy of the diffuse interface method by allowing thinner interfacial thickness to be used in the domain parameter. Here, the SBM-formulated Navier-Stokes equations are solved with the Finite Difference Method on refined mesh systems. Sharp-interface Finite Element Method simulations using the commercial software COMSOL on body-conforming meshes are also provided for comparison. Favorable agreement between the two methods is observed. Since it is no longer necessary for the mesh to conform to the complex geometry, the grid system for the SBM simulations can be generated rapidly and without additional manual interventions, making the entire simulation process more expedient.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Low Cost High Efficiency Magnetrons for Accelerator Applications

High efficiency, low cost RF sources are required for proton, ion, and muon accelerators. These sources must be compact and provide precise control of the output power and phase. Currently only large, expensive klystrons can provide this performance. Calabazas Creek Research Inc. proposes to develop a phase locked magnetron-based system that has phase and amplitude control via a low power amplifier. The system uses phase modulation to control the RF power. The efficiency can exceed 80% and the cost is expected to be less than $3/Watt, significantly lower than other high power amplifiers. CCR originally proposed to develop a magnetron with a grid for control of phase and amplitude. Detailed simulations showed that this was not a promising approach. The grid was found to be viable only in magnetrons with low duty cycle, and amplitude control was demonstrated; but the grid was found to be not effective for phase locking. Attention was turned to a concept from Fermilab, which is very promising for both amplitude and phase control and does not require a grid. CCR will develop an RF system providing phase and amplitude control of a 100 kW peak, 10 kW average 1.3 GHz magnetron. Procedures and techniques will be applicable to design of systems at other frequencies and power levels. The program will include development of the magnetron and locking electronics. The system will be tested at Fermilab. Commercial Applications and Other Benefits Magnetrons can provide high levels of RF power at very high efficiency at low cost. As oscillators, however, their applications are limited. Magnetrons with more precise control of the output power and control of the phase could find wide application in accelerators and colliders. They would also provide improved performance for high resolution radar.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

SU-G-IeP3-09: Investigating the Interplay of Antiscatter Grids with Modern Detectors and Image Processing in Digital Radiography

Purpose: To use phantom and simulation experiments to relate technique factors, patient size and antiscatter grid use to image quality in portable digital radiography (DR), in light of advancements in detector design and image processing. Methods: Image contrast-to-noise ratio (CNR) on a portable DR system (MobileDaRt Evolution, Shimadzu) was measured by imaging four aluminum inserts of varying thickness, superimposed on a Lucite slab phantom using a pediatric abdominal protocol. Three thicknesses of Lucite were used: 6.1cm, 12cm, and 18.2cm, with both 55 and 65 kVp beams. The mAs was set so that detector entrance exposure (DEE) was matched between kVp values. Each technique and phantom was used with and without an antiscatter grid (focused linear grid embedded in aluminum with an 8:1 ratio). The CNR-improvement-factor was then used to determine the thickness- and technique-dependent appropriateness of grid use. Finally, the same experiment was performed via Monte Carlo simulation, integrating incident energy fluence at each detector pixel, so that effects of detector design and image processing could be isolated from physical factors upstream of the detector. Results: The physical phantom experiment demonstrated a clear improvement for the lower tube voltage (55kVp), along with substantial CNR benefits with grid use for 12–18cm phantoms. Neither trend was evident with Monte Carlo, suggesting that suboptimal quantum-detection-efficiency and automated grid-removal could explain trends in kVp and grid use, respectively. Conclusion: Physical experiments demonstrate marked improvement in CNR when using a grid for phantoms of 12 and 18cm Lucite thickness (above ∼10cm soft-tissue equivalent). This benefit is likely due to image processing, as this result was not seen with Monte Carlo. The impact of image processing on image resolution should also be investigated, and the CNR benefit of low kVp and grid use should be weighed against the increased exposure time necessary to achieve adequate DEE.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

A coupled ALE-AMR method for shock hydrodynamics

We present a numerical method combining adaptive mesh refinement (AMR) with arbitrary Lagrangian-Eulerian (ALE) mesh motion for the simulation of shock hydrodynamics on unstructured grids. The primary goal of the coupled method is to use AMR to reduce numerical error in ALE simulations at reduced computational expense relative to uniform fine mesh calculations, in the same manner that AMR has been used in Eulerian simulations. We also identify deficiencies with ALE methods that AMR is able to mitigate, and discuss the unique coupling challenges. The coupled method is demonstrated using three-dimensional unstructured meshes of up to O(10 7 ) tetrahedral cells. Convergence of ALE-AMR solutions towards both uniform fine mesh ALE results and analytic solutions is demonstrated. Speed-ups of 5-10× for a given level of error are observed relative to uniform fine mesh calculations.

42 ENGINEERING↗
DOE OSTI2013

PERPENDICULAR ION HEATING BY REDUCED MAGNETOHYDRODYNAMIC TURBULENCE

Recent theoretical studies argue that the rate of stochastic ion heating in low-frequency Alfvén-wave turbulence is given by Q = c{sub 1}((δu){sup 3}/ρ)exp (– c{sub 2}/ε), where δu is the rms turbulent velocity at the scale of the ion gyroradius ρ, ε = δu/v{sub i}, v{sub i} is the perpendicular ion thermal speed, and c{sub 1} and c{sub 2} are dimensionless constants. We test this theoretical result by numerically simulating test particles interacting with strong reduced magnetohydrodynamic (RMHD) turbulence. The heating rates in our simulations are well fit by this formula. The best-fit values of c{sub 1} are ∼1. The best-fit values of c{sub 2} decrease (i.e., stochastic heating becomes more effective) as the Reynolds number and the number of grid points in the RMHD simulations increase. As an example, in a 1024{sup 2} × 256 RMHD simulation with a dissipation wavenumber of the order of the inverse ion gyroradius, we find c{sub 2} = 0.21. We show that stochastic heating is significantly stronger in strong RMHD turbulence than in a field of randomly phased Alfvén waves with the same power spectrum, because coherent structures in strong RMHD turbulence increase orbit stochasticity in the regions where ions are heated most strongly. We find that c{sub 1} increases by a factor of ∼3 while c{sub 2} changes very little as the ion thermal speed increases from values <<v{sub A} to values ∼v{sub A}, where v{sub A} is the Alfvén speed. We discuss the importance of these results for perpendicular ion heating in the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Historical global Earth System Model simulations with E3SM's dynamic root module

This data package contains global-scale Earth System Model simulations run with DOE's E3SM Model. The package includes one set of simulations run in the default configuration and a second set of simulations run with the dynamic root module enabled. These two datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The outputs are provided here on a 0.5 x 0.5 global grid at monthly resolution. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are broken up into 20 year chunks to facilitate easier read-in. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and GrADS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Short-Term Forecasting of Thermostatic and Residential Loads Using Long Short-Term Memory Recurrent Neural Networks

Internet of Things (IoT) devices in smart grids enable intelligent energy management for grid managers and personalized energy services for consumers. Investigating a smart grid with IoT devices requires a simulation framework with IoT devices modeling. However, there lack comprehensive study on the modeling of IoT devices in smart grids. This paper investigates the IoT device modeling of a thermostatic load and implements the recurrent neural networks model for short-term load forecasting in this IoT-based thermostatic load. The recurrent neural network structure is leveraged to build a load forecasting model on temporal correlation. The temporal recurrent neural network layers including long short-term memory cells are employed to learn the data from both the simulation platform and New South Wales residential datasets. The simulation results are provided for demonstration.

electric load forecasting↗