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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Leveraging a Neural Network-Enhanced Reproducing Kernel Particle Method for Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation has been developed to analyze this system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. Here, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RKPM is additionally used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

degradation↗
DOE OSTI2018

Representation and evolution of urban weather boundary conditions in downtown Chicago

Our study presents a novel computing technique for data exchange and coupling between a high-resolution weather simulation model and a building energy model, with a goal of evaluating the impact of urban weather boundary conditions on energy performance of urban buildings. The Weather Research and Forecasting (WRF) model is initialized with the operational High-Resolution Rapid Refresh (HRRR) dataset to provide hourly weather conditions over the Chicago region. We utilize the building footprint, land use, and building stock datasets to generate building energy models using EnergyPlus. We mapped the building exterior surfaces to local air nodes to import simulated microclimate data and to export buildings' heat emissions to their local environment. Preliminary experiments for a test area in Chicago show that predicted building cooling energy use differs by about 4.7% for the selected date when compared with simulations using TMY weather data and without considering the urban microclimate boundary conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Parametric modeling of energy filtering by energy barriers in thermoelectric nanocomposites

We present a parametric modeling of the thermoelectric transport coefficients based on a model previously used to interpret experimental measurements on the conductivity, σ, and Seebeck coefficient, S, in highly Boron-doped polycrystalline Si, where a very significant thermoelectric power factor (TPF) enhancement was observed. We have derived analytical formalism for the transport coefficients in the presence of an energy barrier assuming thermionic emission over the barrier for (i) non-degenerate and (ii) degenerate one-band semiconductor. Simple generic parametric equations are found that are in agreement with the exact Boltzmann transport formalism in a wide range of parameters. Moreover, we explore the effect of energy barriers in 1-d composite semiconductors in the presence of two phases: (a) the bulk-like phase and (b) the barrier phase. It is pointed out that significant TPF enhancement can be achieved in the composite structure of two phases with different thermal conductivities. The TPF enhancement is estimated as a function of temperature, the Fermi energy position, the type of scattering, and the barrier height. The derived modeling provides guidance for experiments and device design.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Electron phonon coupling in Ni-based binary alloys with application to displacement cascade modeling

Energy transfer between lattice atoms and electrons is an important channel of energy dissipation during displacement cascade evolution in irradiated materials. On the assumption of small atomic displacements, the intensity of this transfer is controlled by the strength of electron–phonon (el–ph) coupling. The el–ph coupling in concentrated Ni-based alloys was calculated using electronic structure results obtained within the coherent potential approximation. It was found that Ni 0.5 Fe 0.5 , Ni 0.5 Co 0.5 and Ni 0.5 Pd 0.5 are ordered ferromagnetically, whereas Ni 0.5 Cr 0.5 is nonmagnetic. Since the magnetism in these alloys has a Stoner-type origin, the magnetic ordering is accompanied by a decrease of electronic density of states at the Fermi level, which in turn reduces the el–ph coupling. Thus, the el–ph coupling values for all alloys are approximately 50% smaller in the magnetic state than for the same alloy in a nonmagnetic state. As the temperature increases, the calculated coupling initially increases. After passing the Curie temperature, the coupling decreases. The rate of decrease is controlled by the shape of the density of states above the Fermi level. Introducing a two-temperature model based on these parameters in 10 keV molecular dynamics cascade simulation increases defect production by 10–20% in the alloys under consideration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

System-of-Systems Approach for Integrated Energy Systems Modeling and Simulation: Preprint

Today’s electricity grid is the most complex system ever built—and the future grid is likely to be even more complex because it will incorporate distributed energy resources (DERs) such as wind, solar, and various other sources of generation and energy storage. The complexity is further augmented by the possible evolution to new retail market structures that provide incentives to owners of DERs to support the grid. To understand and test new retail market structures and technologies such as DERs, demand-response equipment, and energy management systems while providing reliable electricity to all customers, an Integrated Energy System Model (IESM) is being developed at NREL. The IESM is composed of a power flow simulator (GridLAB-D), home energy management systems implemented using GAMS/Pyomo, a market layer, and hardware-in-the-loop simulation (testing appliances such as HVAC, dishwasher, etc.). The IESM is a system-of-systems (SoS) simulator wherein the constituent systems are brought together in a virtual testbed. We will describe an SoS approach for developing a distributed simulation environment. We will elaborate on the methodology and the control mechanisms used in the co-simulation illustrated by a case study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Avista CEF2 Shared Energy Economy: Modeling and Simulation

This research project supported Avista’s Shared Energy Economy (SEE) Project in Spokane’s University District (UDistrict), as funded by the WA Department of Commerce Clean Energy Fund (CEF) Phase 2. The SEE project comprises a microgrid with two campus buildings, two solar photovoltaic generators, and two batteries. The microgrid can operate grid-connected or off-grid. This research project included modeling the buildings and other microgrid components, simulating a transactive energy system, and supporting Avista’s testing of different use cases for the WA Department of Commerce. The main research finding is that buildings can be modeled successfully in a data-driven approach.

14 SOLAR ENERGY↗
DOE OSTI2020

NLR Engage™: A Calliope Web Environment for Collaborative Energy Systems Modeling and Planning [SWR-20-16]

NLR Engage™ is a free, open-access energy system planning tool that allows multiple users/stakeholders to develop and collaborate on capacity expansion models. The tool, developed at the National Laboratory of the Rockies (NLR), provides a collaborative and easy-to-use interface built on Calliope, a multi-scale energy systems modeling framework. Visit the NLR hosted webtool at https://engage.nlr.gov/en/login/?next=/en/

Harris, Tom↗
DOE OSTI2017

Insights on the origin of the Tb5Ge4 magnetocaloric effect

In this report the magnetic, atomic structures and spin-lattice coupling have been thoroughly studied through high magnetic field magnetometry, Synchrotron X-ray diffraction under applied magnetic field and magnetostriction measurements in the Tb5Ge4 compounds. A field induced phase transition from an antiferromagnetic towards a ferromagnetic ordering was confirmed but with absence of structural transformation. This absence has been confirmed experimentally through synchrotron x-ray diffraction under applied field (up to 30 T). Moreover, this absence was explained via a thermodynamic free energy model: first principles calculations determined a large energy gap (ΔE=0.65 eV) between the two possible structures, O(I) and O(II). From magnetic and structural properties, a H-T phase diagram has been proposed for Tb5Ge4. Finally it was observed a large magnetostriction (up to 600 ppm) induced by ΔH=7 T.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Solvophobic and solvophilic contributions in the water-to-aqueous guanidinium chloride transfer free energy of model peptides

We report on the solvation free energy of two different conformations (helix and extended) of two different peptides (deca-alanine and deca-glycine) in two different solvents (water and aqueous guanidinium chloride, GdmCl). The free energies are gained using the quasichemical organization of the potential distribution theorem, an approach that naturally provides the repulsive (solvophobic or cavity) and attractive (solvophilic) contributions to solvation. The solvophilic contribution is further parsed into a chemistry contribution arising from solute interaction with the solvent in the first solvation shell and a long-range contribution arising from non-specific interactions between the solute and the solvent beyond the first solvation shell. The cavity contribution is obtained for two different envelopes, Σ SE , which theory helps identify as the solvent excluded volume, and Σ G , a larger envelope beyond which solute-solvent interactions are Gaussian. The Σ SE envelope is independent of the solvent, as expected on the basis of the insensitivity to the solvent type of the distance of closest approach between protein heavy atoms and solvent heavy atoms, but contrary to the intuition based on treating solvent constituents as spheres of some effective radii. For both envelopes, the cavity contribution in water is proportional to the surface area of the envelope. The same does not hold for GdmCl(aq), revealing the limitation of using molecular area to assess solvation energetics. The Σ G -cavity contribution predicts that GdmCl(aq) should favor the more compact state, contrary to the role of GdmCl in unfolding proteins. The chemistry contribution attenuates this effect, but still the net local (chemistry plus Σ G -packing) contribution is inadequate in capturing the role of GdmCl. With the inclusion of the long-range contribution, which is dominated by van der Waals interaction, aqueous GdmCl favors the extended conformation over the compact conformation. Our result emphasizes the importance of weak, but attractive, long-range dispersion interactions in protein solution thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

The Martian climate: Energy balance models with CO2/H2O atmospheres

Progress in the development of a multi-reservoir, time dependent energy balance climate model for Mars driven by prescribed insolation at the top of the atmosphere is reported. The first approximately half-year of the program was devoted to assembling and testing components of the full model. Specific accomplishments were made on a longwave radiation code, coupling seasonal solar input to a ground temperature simulation, and conceptualizing an approach to modeling the seasonal pressure waves that develop in the Martian atmosphere as a result of sublimation and condensation of CO2 in polar regions.

Hoffert, M. I.↗
NASA NTRS1991

A nuclear fragmentation energy deposition model

A formalism for target fragment transport is presented with application to energy loss spectra in thin silicon devices. A nuclear data base is recommended that agrees well with the measurements of McNulty et al. using surface barrier detectors. High-energy events observed by McNulty et al., which are not predicted by intranuclear cascade models, are well represented by the present work.

NASA Discipline Number 04-10↗
DOE OSTI2020

Integrated Transportation-Energy Systems Modeling

Transportation is currently the least-diversified energy demand sector, with over 90% of global transportation energy use coming from petroleum product. After over a century of petroleum dominance, however, many leading experts anticipate major electrification trends that could disrupt the transportation energy demand landscape. These changes in electricity demand complement profound changes happening within electric power supply systems, including integration of variable renewables, distributed generation and storage, and greater participation in power system planning and operations from traditionally passive consumers. This broader context underscores the importance of understanding how transportation electrification will impact electricity demand, including changes in the load shapes that characterize the system and the opportunity to leverage flexible EV charging to more cost-effectively balance demand and supply. This talk provides an overview of recent findings on infrastructure requirements to support EV adoption, integration challenges and the impact of EV on power systems, and opportunities to leverage flexible (or smart) EV charging to support power system planning and operations.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2014

Oneida Tribe of Indians of Wisconsin Energy Optimization Model

Oneida Nation is located in Northeast Wisconsin. The reservation is approximately 96 square miles (8 miles x 12 miles), or 65,000 acres. The greater Green Bay area is east and adjacent to the reservation. A county line roughly splits the reservation in half; the west half is in Outagamie County and the east half is in Brown County. Land use is predominantly agriculture on the west 2/3 and suburban on the east 1/3 of the reservation. Nearly 5,000 tribally enrolled members live in the reservation with a total population of about 21,000. Tribal ownership is scattered across the reservation and is about 23,000 acres. Currently, the Oneida Tribe of Indians of Wisconsin (OTIW) community members and facilities receive the vast majority of electrical and natural gas services from two of the largest investor-owned utilities in the state, WE Energies and Wisconsin Public Service. All urban and suburban buildings have access to natural gas. About 15% of the population and five Tribal facilities are in rural locations and therefore use propane as a primary heating fuel. Wood and oil are also used as primary or supplemental heat sources for a small percent of the population. Very few renewable energy systems, used to generate electricity and heat, have been installed on the Oneida Reservation. This project was an effort to develop a reasonable renewable energy portfolio that will help Oneida to provide a leadership role in developing a clean energy economy. The Energy Optimization Model (EOM) is an exploration of energy opportunities available to the Tribe and it is intended to provide a decision framework to allow the Tribe to make the wisest choices in energy investment with an organizational desire to establish a renewable portfolio standard (RPS).

14 SOLAR ENERGY↗
DOE OSTI2024

The Challenges of Modeling Distributed Energy Resources (DERs) as Blackstart Resources and for Volt-VAR Optimality

Modeling, testing and instituting Distributed Energy Resources (DERs) as Blackstart Resoucrces presents several challenges due to the fundamental differences between traditional black start resources (e.g., large generators) versus DERs like solar PV systems with battery storage. This paper addresses some of these key challenges. These include intermittency of coordinating DERs to provide continuous power during a black start event, especially during extended periods of cloud cover or when battery energy storage is depleted. This paper additionally addresses the collapsing voltage and stability control challenges specific to maintaining bulk power system stability during black start synchronization These physical and engineering limitations require careful engineering design, modeling and engineering to ensure that DERs can support critical loads and substations during black start events. A variety of additional challenges also exist. Additionally, there are challenges associated with feeder location and low voltage secondary system impacts on DER functions and settings. We compare typical functions and settings for DERs for power factor control and correction. We also demonstrate how voltag control via Volta-VAR power factor correction can be done

Mukherjee, Srijib↗
DOE OSTI2016

Numerical Investigation of Spark Ignition Events in Lean and Dilute Methane/Air Mixtures using a Detailed Energy Deposition Model

It is beneficial but challenging to operate spark-ignition engines under highly lean and dilute conditions. The unstable ignition behavior can result in downgraded combustion performance in engine cylinders. Numerical approach is serving as a promising tool to identify the ignition requirements by providing insight into the complex physical/chemical phenomena. An effort to simulate the early stage of flame kernel initiation in lean and dilute fuel/air mixture has been made and discussed in this paper. The simulations are set to validate against laboratory results of spark ignition behavior in a constant volume combustion vessel. In order to present a practical as well as comprehensive ignition model, the simulations are performed by taking into consideration the discharge circuit analysis, the detailed reaction mechanism, and local heat transfer between the flame kernel and spark plug. The energy profile and the energy source geometry are investigated in detail to represent the physics of electrical discharge. It was observed in the experiments that a sufficiently high ambient pressure is necessary for a successful ignition event in the lean and dilute mixture when the spark plug gap size and primary energy input are held constant. By adopting realistic energy levels, this detailed energy deposition model showed the capability to reasonably present such ignition behavior transition. The unique combination of energy deposition profile and geometry reveals the complexity of electrical discharge during the spark ignition event. The response of the combustible gas to the energy deposition showed dependency on the volumetric energy density, energy source’s surface area, temperature gradient at the energy source boundary, as well as the heat transfer condition local to the flame kernel.

Zhang, Anqi↗
DOE OSTI2023

Hydropower Energy Storage Capacity (HESC) Dataset

The Hydropower Energy Storage Capacity (HESC) Dataset catalogs characteristics that are relevant to evaluating reservoir storage and estimates of energy storage capacity based on varying levels of detail. Hydropower dams and reservoirs were included based on information from the National Inventory of Dams (NID; USACE, 2021) and Global Reservoir and Dam (GRanD v1.3) and Existing Hydropower Assets datasets. These data provide a foundation for understanding available resources at existing hydropower facilities and their potential to provide storage of energy and more flexible generation. Estimates of energy storage capacity include: • Level 1 – nominal energy storage capacity based on maximum storage capacities and hydraulic head • Level 2 – nominal energy storage capacity based on historical models or observations of reservoir volume and hydraulic head. These estimates are provided based on capacity from the entire historical period as well as monthly values. • Level 3 – modeled energy generation based on volume-elevation relationships, historical storage, observed/modeled inflows, and hydraulic capacity of turbines and calculated both as overall and on a monthly basis. • Level 4 – modeled energy generation incorporating information from Level 3 and operational constraints. For facilities where installed capacity is known, there are also estimates for discharge duration (the length of time when a facility could provide generation at a given capacity).

13 HYDRO ENERGY↗
DOE OSTI2017

Model calibration of a variable refrigerant flow system with a dedicated outdoor air system: A case study

With increased use of variable refrigerant flow (VRF) systems in the U.S. building sector, interests in capability and rationality of various building energy modeling tools to simulate VRF systems are rising. This paper presents the detailed procedures for model calibration of a VRF system with a dedicated outdoor air system (DOAS) by comparing to detailed measured data from an occupancy emulated small office building. The building energy model is first developed based on as-built drawings, and building and system characteristics available. The whole building energy modeling tool used for the study is U.S. DOE’s EnergyPlus version 8.1. The initial model is, then, calibrated with the hourly measured data from the target building and VRF-DOAS system. In a detailed calibration procedures of the VRF-DOAS, the original EnergyPlus source code is modified to enable the modeling of the specific VRF-DOAS installed in the building. After a proper calibration during cooling and heating seasons, the VRF-DOAS model can reasonably predict the performance of the actual VRF-DOAS system based on the criteria from ASHRAE Guideline 14-2014. The calibration results show that hourly CV-RMSE and NMBE would be 15.7% and 3.8%, respectively, which is deemed to be calibrated. As a result, the whole-building energy usage after calibration of the VRF-DOAS model is 1.9% (78.8 kWh) lower than that of the measurements during comparison period.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗