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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Process-Based Balance-of-System Cost Modeling for Offshore Wind Power Plants in the United States: Preprint

This work describes the development of a process based and open source balance of system cost model which provides the capability to evaluate both existing and novel offshore wind technologies. Individual design and installation steps are represented with bottom-up engineering models that compute the times and costs associated with the process; furthermore, operational constraints are assigned to each process so that delays due to weather and presence of marine mammals may be accounted for in the overall project timeline. The model structure, assumptions, inputs, and results are vetted with industry partners and compared against actual projects for validation; installation times are shown to agree with real data with relative errors of less than 35\%. Case studies are presented to demonstrate the functionality of the model. First, individual vessel efficiencies are computed for varying numbers of installation vessels and weather time series to show the diminishing returns of more than two feeder barges. Then, array cable capital costs and installation times are determined for a representative project with different turbine sizes. This quantifies the cost benefit tradeoffs of decreasing number of turbines, increased turbine spacing, and fewer turbine terminations and shows a net cost savings. These results demonstrate that the BOS model features the accuracy, functionality, and accessibility to serve as the foundation for a wide range of analyses to identify cost reduction potentials for offshore wind energy in the United States.

17 WIND ENERGY↗
DOE OSTI2018

Nonlinear model-based controller for premixed charge compression ignition combustion timing in diesel engines

Advanced combustion modes, such as PCCI, operate near the system stability limits. In PCCI, the combustion event begins without a direct combustion trigger in contrast to traditional spark-ignited gasoline engines and direct-injected diesel engines. The lack of a direct combustion trigger encourages the usage of model-based controls to provide robust control of the combustion phasing. The nonlinear relationships between the control inputs and the combustion system response often limit the effectiveness of traditional, non-model-based controllers. Accurate knowledge of the system states and inputs is helpful for implementation of an effective nonlinear controller. A nonlinear controller is developed and implemented to control the engine combustion timing during diesel PCCI operation by targeting desired values of the in-cylinder oxygen concentration, pressure, and temperature during early fuel injection.

42 ENGINEERING↗
DOE OSTI2020

Probabilistic evolution of stochastic dynamical systems: A meso-scale perspective

Stochastic dynamical systems arise naturally across nearly all areas of science and engineering. Typically, a dynamical system model is based on some prior knowledge about the underlying dynamics of interest in which probabilistic features are used to quantify and propagate uncertainties associated with the initial conditions, external excitations, etc. From a probabilistic modeling standing point, two broad classes of methods exist, i.e. macro-scale methods and micro-scale methods. Classically, macro-scale methods such as statistical moments-based strategies are usually too coarse to capture the multi-mode shape or tails of a non-Gaussian distribution. Micro-scale methods such as random samples-based approaches, on the other hand, become computationally very challenging in dealing with high-dimensional stochastic systems. In view of these potential limitations, a meso-scale scheme is proposed here that utilizes a meso-scale statistical structure to describe the dynamical evolution from a probabilistic perspective. The significance of this statistical structure is twofold. First, it can be tailored to any arbitrary random space. Second, it not only maintains the probability evolution around sample trajectories but also requires fewer meso-scale components than the micro-scale samples. To demonstrate the efficacy of the proposed meso-scale scheme, a set of examples of increasing complexity are provided. Connections to the benchmark stochastic models as conservative and Markov models along with practical implementation guidelines are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Modeling Flexible Generator Operating Regions via Chance- constrained Stochastic Unit Commitment

Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.

42 ENGINEERING↗
DOE OSTI2017

Model-Based Characterization of High Temperature Oxy-Coal Combustion Systems

Reaction Engineering International (REI) is leading a DOE-funded program focused on characterization of the impacts of high temperatures and pressures in oxy-coal combustion systems. The objective is to produce data and validate mechanisms to describe and predict flame behavior, heat transfer, ash deposition and ash chemistry to enable application of these advanced combustion technologies in full-scale systems. This presentation will provide an overview of accomplishments achieved to date on this project and present modeling results of high temperature oxy-coal combustion using undiluted directed oxygen with minimal flue gas recirculation at atmospheric pressure. Comparisons of model results and experimental data from 100 kW and 1.5 MW test furnaces will be provided for gas and wall temperatures, wall heat flux, carbon on ash, ash deposition rates and ash chemistry.

high temperature, modeling↗
DOE OSTI2018

KiteFAST

KiteFAST is a simulator for airborne wind energy systems based on NREL's OpenFAST whole turbine simulator. KiteFAST is a multi-physics engineering tool for modeling the coupled aero-servo-elastic dynamics of airborne wind energy systems i.e. a wind-energy kite. The engineering model is like NREL's OpenFAST tool for land-based or offshore horizontal-axis wind turbines atop towers, in that KiteFAST models the important physical phenomena and system couplings, including the wind/aerodynamic excitation and full-system dynamics response (fuselage, wings, tail, stabilizers, pylons, nacelles, rotors, tether, ground station, control surfaces, and controller) under both normal (for fatigue) and extreme (for ultimate) loading conditions. The configuration of the wind-energy kite is assumed to have one fuselage; two wings (starboard, port) attached to the fuselage; one vertical stabilizer attached the fuselage; two horizontal stabilizers (starboard, port) attached to the vertical stabilizer; one or more pylons per wing, each with two rotors (top, bottom); one ground-station-fixed tether with a bridal connection to the wings, and nominal circular motion of the energy kite in the port (left) direction. The general configuration of the control surfaces assumes one or more flaps per wing, two rudders on the vertical stabilizer, two elevators per horizontal stabilizer, and rotors with variable speed and rotor-collective blade pitch. KiteFAST was developed from (1) the existing MBDyn open-source multi-body dynamics code; (2) the existing/modified OpenFAST modules NWTC Subroutine Library, AirfoilInfo, InflowWind, MoorDyn, and TurbSim; and (3) new source code for a) generating MBDyn models of the energy kite (KiteMBDyn Preprocessor), b) computing quasi-steady energy-kite aerodynamics (KiteAeroDyn, KiteAeroDyn Driver, KiteVSM, ActuatorDisk), c) interfacing an energy-kite controller, and d) coupling the various KiteFAST modules together (KiteFASTMBD).

Jonkman, Jason↗
DOE OSTI2025

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗
DOE OSTI2024

Incorporating Wind Turbine Choice in High-Resolution Geospatial Supply Curve and Capacity Expansion Models

To achieve national decarbonization goals, U.S. annual deployment of wind energy will need to increase by at least fivefold compared to the recent past. Modeling and analysis frameworks can help inform where and how wind energy deployment might occur and thereby help enable the achievement of decarbonization goals. However, most prior wind energy modeling and analysis studies rely on generalized representations of wind energy technologies. Since wind energy technology advancements are expected to increase the competitiveness of wind energy, it is important to incorporate more detailed representations of turbine technology into wind energy modeling. Here we present a new method that incorporates wind turbine choice into the technology representation of land-based wind energy in long-term planning models. Our method integrates three previously published modeling and analysis capabilities: 1) bottom-up cost modeling to estimate future technology costs, 2) geospatial modeling to represent siting decisions, and 3) power sector modeling to evaluate potential deployment. We refer to this approach as a "customized turbine choice" methodology because it creates a composite turbine scenario by choosing from multiple wind turbine technologies—using site-specific optimized turbine layout and selecting the least-cost technology at each location. We demonstrate the capabilities of this new modeling pipeline by examining how the selection of four different wind turbine configurations might evolve from 2021 through 2040. Our results show that using our customized turbine choice methodology could lead to higher estimates for wind future deployment, which indicates that more simplified modeling might underestimate the role that wind energy could play in meeting decarbonization goals. Future research is needed to further explore the implications of turbine choice and to better inform technology researchers, original equipment manufacturers, and other wind industry stakeholders about the market potential of different wind turbine technologies.

17 WIND ENERGY↗
DOE OSTI2025

Multiscale Modeling of the Mechanical Response of Silicon Carbide Composite Within the Accelerated Fuel Qualification Framework

The accelerated fuel qualification (AFQ) framework has been used for the initial development of multiscale modeling of silicon carbide (SiC) fiber reinforced composite (SiC-SiC). The AFQ framework provides a methodology to leverage physics-informed multiscale modeling along with a reduced set of empirical test data to reduce the time and cost of licensing and qualification of new nuclear fuel systems while maintaining the overall nuclear power plant safety case. SiC-SiC is being proposed for in-core applications, most notably fuel cladding, for current and next-generation nuclear reactors because of its high temperature stability, irradiation tolerance, and ability to withstand many accident conditions. As these composites exhibit multiscale architectures and complex microstructure-based fracture mechanics, it is an appealing use case for the AFQ methodology. While the end goal of this work is a single multiscale model that can be used for predictive in-core performance, current focus is on the individual various length scale models. Four individual models have been initially developed from microscale to engineering system level to capture key physics-based effects across different length scales. These models include a microscale homogenized tow model, a mesoscale fast Fourier transform–based weave model that integrates the homogenized tow model, a mesoscale finite element–based weave model, and a system-level BISON fuel performance model. Results of these models have undergone an initial comparison with separate-effects test data showing a good match to experimental results. By using the AFQ framework during model development, several near-term benefits have been secured including a reduction in development time for the SiC-SiC cladding, more targeted irradiation testing, and a better understanding of uncertainty.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

What Questions Would a Systems Engineer Ask to Assess Systems Engineering Models as Credible

Digital Systems Engineering strategies typically call for digital Systems Engineering models to be retained in repositories and certified as an authoritative source of truth (enabling model reuse, qualification, and collaboration). In order for digital Systems Engineering models to be certified as authoritative (credible), they need to be assessed - verified and validated - and with the amount of uncertainty in the model quantified (consider reusing someone else's model without knowing the author). Due to this increasing model complexity, the authors assert that traditional human-based methods for validating, verifying, and uncertainty quantification - such as human-based peer-review sessions - cannot sufficiently establish that a digital Systems Engineering model of a complex system is credible. Digital Systems Engineering models of complex systems can contain millions of nodes and edges. The authors assert that this level of detail is beyond the ability of any group of humans - even working for weeks at a time - to discern and catch every minor model infraction. In contrast, computers are highly effective at discerning infractions with massive amounts of information. The authors suggest that a better approach might be to focus the humans at what model patterns should be assessed and enable the computer to assess the massive details in accordance with those patterns - by running through perhaps 100,000 test loops. In anticipation of future projects to implement and automate the assessment of models at Sandia National Laboratories, a study was initiated to elicit input from a group of 25 Systems Engineering experts. The authors positioning query began with - 'What questions would a Systems Engineer ask to assess Systems Engineering models for credibility?" This report documents the results of that survey.

42 ENGINEERING↗
DOE OSTI2018

Integrated Boosting and Hybridization for Extreme Fuel Economy and Downsizing

The objective of this project was to develop, demonstrate, and evaluate commercialization of a highly efficient downsized engine by electrification of the air delivery and waste heat recovery system and optimizing energy usage to achieve significant fuel economy improvement at a commercially viable cost. The system consists of an Electrically Assisted Variable speed Supercharger (EAVS), driven by an electric motor and the engine through a planetary gear train, that provides engine boost pressure and provides the mild hybrid functions of engine start/stop, torque assist, and brake energy recovery. In the exhaust path of the engine is the electric Waste Heat Recovery (eWHR) system, a roots-based expander driven by another electric motor, that enables exhaust gas energy recovery along with controlled back pressure on the engine. The two electric motors are powered by a 48V rechargeable lithium-ion battery. Further, the EAVS system coupled to an EGR valve enables very precise high exhaust recirculation rates to control the NOx emissions. Through two budget periods, the project team of Eaton, Isuzu, Southwest Research Institute and AVL designed and developed the EAVS and eWHR systems, integrated with an Isuzu diesel engine, and validated the target fuel economy performance and emissions by engine dynamometer testing and vehicle level simulations. GT Power model-based analyses results were used to size the EAVS and eWHR systems for the 1.9L Isuzu Spark engine. The two systems were built and the functional testing was carried out to verify the boosting performance of the superchargers. Following the baseline engine dynamometer testing, the two systems were integrated with the engine and the fuel economy performance and emissions were determined by combined steady state and transient testing over three drive cycles, namely, FTP75, NEDC and HWFET. The EAVS/eWHR system demonstrated 4% improvement in fuel economy for the NEDC cycle in engine dyno testing, correlating well with vehicle simulation results (5.3%). The simulation results indicated that the combination of hybrid functions and drivetrain optimization, fuel economy improvement of more than 20% was feasible with the system. The commercialization study to evaluate the cost of the system and the scalability for different engine/vehicle classes was planned for the final budget period but not completed as the project was closed at the end of budget period two.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Optimized piston temperature control in gaseous fuel hydrogen engine system

Operating a gaseous fuel engine system includes combusting a mixture containing a gaseous hydrogen fuel and air in a cylinder of an engine, varying an operating parameter of the engine to which a crown surface temperature of a piston within the cylinder is responsive, and populating a temperature model based on a value of the varied operating parameter. Operating a gaseous fuel engine system further includes operating an oil spray apparatus to spray oil onto the piston based on the populated temperature model, and maintaining the crown surface temperature of the piston between a high temperature limit and a pre-ignition mitigation temperature limit based on the operating of the oil spray apparatus. Related apparatus and control logic is also disclosed.

Bochart, Michael R.↗
DOE OSTI2017

Coupled THMC models for bentonite in an argillite repository for nuclear waste: Illitization and its effect on swelling stress under high temperature

Subsurface manipulations such as those expected from the disposal of heat-emanating radioactive waste in deep repositories can induce strongly coupled Thermal (T), hydrological (H), mechanical (M) and chemical (C) processes. Adequate coupled THMC models are highly desirable or even indispensable for performance assessment of such repositories, for examples for the analysis of bentonite-based engineered barrier system (EBS) surrounding the emplaced waste. In this study, we present coupled THMC model simulations of a generic nuclear waste repository in an argillite with a bentonite-based buffer. The objective is to evaluate the chemical changes in the EBS bentonite and their effect on mechanical behavior under high temperature, attempting to shed light on whether EBS bentonite can sustain temperatures higher than 100 °C without significant impact on barrier's performance. Two scenarios were simulated for comparison: a case in which the temperature near the waste canister peaks at 200 °C and a case in which the temperature at the same spot culminate with about 100 °C. Simulations for a generic case with Kunigel-VI bentonite as backfill and Opalinus Clay as host rock were conducted for 1000 years and reported in the previous study (Zheng et al., 2015). In this paper, simulations for 100,000 years have been done for two types of bentonite-based buffer materials: Kunigel-VI and FEBEX bentonite. This enables us to evaluate how different types of bentonite behave in terms of the illitization and its impact on swelling stress and whether we can generalize these results to support decision making. The simulations show the occurrence of illitization in the bentonite buffer and the enhancement of illitization under high temperature. However, FEBEX bentonite undergoes less illitization mainly due to the higher ion concentration in pore water and the lower content of K-feldspar in the bentonite mineral composition. Moreover, the reduction of swelling stress by chemical changes is more pronounced for Kunigel-VI bentonite than for FEBEX bentonite. Furthermore, the results of our model simulations suggest that an argillite repository with a bentonite-based EBS that is similar to FEBEX bentonite could sustain temperatures much higher than 100 °C as far as illitization concerns. Model results also reveal that illitization is stabilized after about 2000 years in bentonite near the waste package, but continues in bentonite near the bentonite-argillite interface, which manifests the strong effect of geochemical interaction between EBS bentonite and host rock on long term illitization in bentonite.

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

Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. Here this article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

42 ENGINEERING↗
DOE OSTI2018

Model-Based Characterization of Elevated Temperature and High Pressure Oxy-Coal Combustion Systems

Reaction Engineering International is leading a DOE-funded program focused on characterization of the impacts of high temperatures and pressures in oxy-coal combustion systems. A primary objective is to evaluate flame behavior, heat transfer, and ash chemistry at high pressure to facilitate the application of pressurized oxy-coal in full-scale systems. The University of Utah’s 300 kW pressurized entrained flow gasifier has been successfully modified and operated as a high pressure, slurry-fed, oxy-coal combustor at firing rates ranging from nearly 100 kW to over 180 kW with reactor pressures as high as 200 psi. This presentation will describe the modifications to the gasifier to allow it to operate as a high pressure, oxy-coal combustor; detail experimental data including measurements of radiant flux, wall surface temperatures, and ash aerosol characterization; and CFD modeling of the experimental conditions. In addition, an update will be provided for accomplishments achieved to date for the component of the program focused on modeling of high temperature oxy-coal combustion using undiluted directed oxygen with minimal flue gas recirculation at atmospheric pressure.

CFD modeling↗
DOE OSTI2024

Optimizing Batch Crystallization with Model-based Design of Experiments

Adaptive and self-optimizing intelligent systems such as digital twins are increasingly important in science and engineering. Digital twins utilize mathematical models to provide added precision to decision-making. However, physics-informed models are challenging to build, calibrate, and validate with existing data science methods. Model-based design of experiments (MBDoE) is a popular framework for optimizing data collection to maximize parameter precision in mathematical models and digital twins. In this work, we apply MBDoE, facilitated by the open-source package Pyomo.DoE, to train and validate mathematical models for batch crystallization. We quantitatively examined the estimability of the model parameters for experiments with different cooling rates. This analysis provides a quantitative explanation for the heuristic of using multiple experiments at different cooling rates.

Lynch, Hailey↗
DOE OSTI2015

Advancement of Systems Designs and Key Engineering Technologies for Materials Based Hydrogen Storage

UTRC lead the development of the Simulink Framework model that enables a comparison of different hydrogen storage systems on a common basis. The Simulink Framework model was disseminated on the www.HSECoE.org website that is hosted by NREL. UTRC contributed to a better understanding of the safety aspects of the proposed hydrogen storage systems. UTRC also participated in the Failure Mode and Effect Analysis of both the chemical- and the adsorbent-based hydrogen storage system during Phase 2 of the Hydrogen Storage Engineering Center of Excellence. UTRC designed a hydrogen storage system with a reversible metal hydride material in a compacted form for light-duty vehicles with a 5.6 kg H2 storage capacity, giving it a 300 miles range. It contains a heat exchanger that enables efficient cooling of the metal hydride material during hydrogen absorption in order to meet the 3.3 minute refueling time target. It has been shown through computation that the kinetics of hydrogen absorption of Ti-catalyzed NaAlH4 was ultimately limiting the rate of hydrogen absorption to 85% of the material capacity in 3.3 minutes. An inverse analysis was performed in order to determine the material property requirements in order for a metal hydride based hydrogen storage system to meet the DOE targets. Work on metal hydride storage systems was halted after the Phase 1 to Phase 2 review due to the lack of metal hydride materials with the required material properties. UTRC contributed to the design of a chemical hydrogen storage system by developing an adsorbent for removing the impurity ammonia from the hydrogen gas, by developing a system to meter the transport of Ammonia Borane (AB) powder to a thermolysis reactor, and by developing a gas-liquid-separator (GLS) for the separation of hydrogen gas from AB slurry in silicone oil. Stripping impurities from hydrogen gas is essential for a long life of the fuel cell system on board of a vehicle. Work on solid transport of AB was halted after the Phase 1 to Phase 2 review in favor of studying the slurry-form of AB as it appeared to be difficult to transport a solid form of AB through the thermolysis reactor. UTRC demonstrated the operation of a compact GLS in the laboratory at a scale that would be required for the actual automotive application. The GLS met the targets for weight and volume. UTRC also reported about the unresolved issue associated with the high vapor pressure of fluids that could be used for making a slurry-form of AB. Work on the GLS was halted after the Phase 2 to Phase 3 review as the off-board regeneration efficiency of the spent AB was below the DOE target of 60%. UTRC contributed to the design of an adsorbent-based hydrogen storage system through measurements of the thermal conductivity of a compacted form of Metal Organic Framework (MOF) number 5 and through the development and sizing of a particulate filter. Thermal conductivity is important for the design of the modular adsorbent tank insert (MATI), as developed by Oregon State University (OSU), in order to enable a rapid refueling process. Stringent hydrogen quality requirements can only be met with an efficient particulate filtration system. UTRC developed a method to size the particulate filter by taking into account the effect of the pressure drop on the hydrogen adsorption process in the tank. UTRC raised awareness about the potential use of materials-based H2 storage systems in applications outside the traditional light-duty vehicle market segment by presenting at several conferences about niche application opportunities in Unmanned Aerial Vehicles (UAV), Autonomous Underwater Vehicles (AUV), portable power and others.

08 HYDROGEN↗