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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Identification of state variables and dynamic inflow from rotor model dynamic tests

The paper describes methods for extracting unknown state variables and parameters from dynamic rotor model tests given transient cyclic pitch stirring inputs, blade root flap-bending measurements, and the form of the dynamic rotor equations, including a rotor dynamic inflow description, when none of the physical parameters are known. A simplified version of the maximum likelihood method seems best suited for this purpose. The measurement equation error covariance matrix is assumed constant during each iteration, but updated for the subsequent iteration. A detailed analysis of the suitability of the derived techniques for studying various rotor dynamic inflow effects is provided.

Banerjee, D.↗
NASA NTRS1976

Space shuttle lift-off dynamic model

Previously developed dynamic models for the calculation of lift-off dynamic response of the space shuttle vehicle can handle only response of the vehicle with eight holddown arms attached or with all holddown arms detached. The new model developed in the referenced report takes into account the transition period between holddown and lift-off by giving the model the ability to vary holddown point separation as a function of vehicle flexible body and rigid body motion. This report documents a study made to verify the new model's capability to simulate vehicle response at lift-off. To do this, a finite element model of the skirt is made and coupled to the free-free modes of the vehicle and cantilevered modes calculated and compared with the previously developed model. Results indicate that the new model will be able to predict accurate vehicle loads.

Christian, D.↗
DOE OSTI2018

Model Order Reduction of Nonviscously Damped Structural Dynamic Models

A reduced order modeling capability has been developed to reduce the computational burden associated with time-domain solutions of structural dynamic models with linear viscoelastic materials. The discretized equations-of-motion produce convolution integrals resulting in a linear system with nonviscous damping forces. The challenge associated with the reduction of nonviscously damped, linear systems is the selection and computation of the appropriate modal basis to perform modal projection. The system produces a nonlinear eigenvalue problem that is challenging to solve and requires use of specialized algorithms not readily available in commercial finite element packages. This SAND report summarizes the LDRD discoveries of a reduction scheme developed for monolithic finite element models and provides preliminary investigations to extensions of the method using component mode synthesis. In addition, this report provides a background overview of structural dynamic modeling of structures with linear viscoelastic materials, and provides an overview of a new code capability in Sierra Structural Dynamics to output the system level matrices computed on multiple processors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

DOE WPTO FY2021 Seedling End Report: Coupling Soil-Foundation Models to MHK Device Dynamic Models to Tighten the Design Envelope

The purpose of this Seedling project is to couple a marine renewable energy (MRE) dynamics simulation software with the soil-foundation models in the OC6 Phase II project [Bergua et al., 2021] and evaluate the software’s performance. This is a first step to accurately evaluating soil-foundation impacts on other types of MRE, like wave or current energy converters (WECs, CECs). OC6 Phase II compares offshore wind turbine (OWT) simulations using several different soil-foundation models to identify and fill key gaps in soil-foundation analyses. WEC-Sim was chosen to model the OC6 Phase II offshore wind turbine and various load cases because of its adaptability, accuracy of hydrodynamic loads, and ability to apply an arbitrary wind loading. Of the four methods used in OC6, the apparent fixity soil-foundation method was coupled with WEC-Sim. Technical challenges with flexible hydrodynamic bodies, added mass and external function libraries inhibited the ability to compare the WEC-Sim results to other OC6 participants. These challenges required that the WEC-Sim model of the OC6 OWT use a combination of rigid and flexible bodies to ensure a numerically stable solution. The rigid monopile creates a more stiff system and causes smaller amplitude motion under hydrodynamic loading and higher dominant frequency of motion under wind loading. These discrepancies are expected based on the increased stiffness of the WEC-Sim case.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

AI-Based EMT Dynamic Model of PV Systems

Several electromagnetic transient (EMT) dynamic modeling methods are available to model systems like photovoltaic (PV) plants, wind power plants, variable-speed drives, among others. The methods include: (a) physics-based models and (b) data-driven models. The physics-based dynamic models may include high-fidelity switched system model and average-value model that both require the control algorithms included in the models. However, manufacturers typically prefer to provide black-box models to avoid disclosing proprietary. One of the solutions to prevent disclosing control algorithms is the use of data-driven dynamic EMT models of PV systems. In this paper, data-driven dynamic EMT model based on artificial intelligence (AI) algorithms are presented. The AI algorithms evaluated include convolutional neural networks, recurrent neural networks, and nonlinear auto-regressive exogenous model. Automation in generating data and training these models is also discussed in this paper. The results generated by the best AI algorithms have been observed to be greater than 95 % accurate.

Debnath, Suman↗
DOE OSTI2019

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO 2 Capture Using Pilot-Plant Data

This paper is focused on the development and validation of a dynamic model for an MEA-based CO 2 capture unit. Starting with a rigorous steady-state process model, the dynamic model is developed in Aspen Plus Dynamics ® using a modified Murphree-efficiency approach and is validated using dynamic data collected from the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The dynamic test runs were designed with due consideration of process excitation and process nonlinearities constrained by the available time to conduct the test runs and implement the experimental designs in the plant control system. The experimental data include solvent composition and loading. Since the experimental data were found to violate mass and energy balances, filtering algorithms coupled with dynamic data reconciliation techniques were used. Without adjusting any model parameters, the dynamic model satisfactorily predicted dynamic response of CO 2 capture due to step changes in the solvent flowrate, flue gas flowrate, and steam flowrates. Transient studies show that the process gain and time constants can considerably change depending on the direction of the disturbance or manipulated variables, indicating process nonlinearities. Due to a storage tank between the absorber and stripper, the time constant of the full plant can be considerably longer than the time constants of the absorber or stripper individually. Furthermore, impact of the control system on the process efficiency while following an optimal CO 2 capture schedule was also studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Lessons from a large-scale systems dynamics modeling project: the example of the biomass scenario model

The biomass scenario model (BSM) is a dynamic model of the biomass-to-biofuels supply chain in the U.S.A., developed during a multi-year analysis effort conducted by the National Renewable Energy Laboratory (NREL), under sponsorship from the United States Department of Energy (DOE) Bioenergy Technologies Office (BETO). The BSM project, which received the 2018 Applications Award by the International System Dynamics Society, has supported collaborative analyses, developed scenarios for industry development and facilitated stakeholder engagement. We summarize insights gained from the BSM project that may be useful to other large-scale dynamic modeling efforts. We summarize the project focus, the analysis process, key outcomes and observations on successful execution of such a product. Key points include the value of a multidisciplinary team with clear roles, engagement of experts and stakeholders, and use and reuse of simple, modular structures. As a result, the overall effort suggests that these practices may aid long-term, team-focused, multi-stakeholder modeling efforts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

A System Dynamics Model of Early-Stage Transition Dynamics in the Bioproducts Industry

The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the techno-economic attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and end use factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) demand. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2004

Overview of the GRC Stirling Convertor System Dynamic Model

A Stirling Convertor System Dynamic Model has been developed at the Glenn Research Center for controls, dynamics, and systems development of free-piston convertor power systems. It models the Stirling cycle thermodynamics, heat flow, gas, mechanical, and mounting dynamics, the linear alternator, and the controller. The model's scope extends from the thermal energy input to thermal, mechanical dynamics, and electrical energy out, allowing one to study complex system interactions among subsystems. The model is a non-linear time-domain model containing sub-cycle dynamics, allowing it to simulate transient and dynamic phenomena that other models cannot. The model details and capability are discussed.

Lewandowski, Edward J.↗
NASA NTRS1993

A local dynamic model for large eddy simulation

The dynamic model is a method for computing the coefficient C in Smagorinsky's model for the subgrid-scale stress tensor as a function of position from the information already contained in the resolved velocity field rather than treating it as an adjustable parameter. A variational formulation of the dynamic model is described that removes the inconsistency associated with taking C out of the filtering operation. This model, however, is still unstable due to the negative eddy-viscosity. Next, three models are presented that are mathematically consistent as well as numerically stable. The first two are applicable to homogeneous flows and flows with at least one homogeneous direction, respectively, and are, in fact, a rigorous derivation of the ad hoc expressions used by previous authors. The third model in this set can be applied to arbitrary flows, and it is stable because the C it predicts is always positive. Finally, a model involving the subgrid-scale kinetic energy is presented which attempts to model backscatter. This last model has some desirable theoretical features. However, even though it gives results in LES that are qualitatively correct, it is outperformed by the simpler constrained variational models. It is suggested that one of the constrained variational models should be used for actual LES while theoretical investigation of the kinetic energy approach should be continued in an effort to improve its predictive power and to understand more about backscatter.

Ghosal, Sandip↗
DOE OSTI2017

Reactive molecular dynamics models from ab initio molecular dynamics data using relative entropy minimization

Here, we present two new multiscale molecular dynamics (MS-RMD) models for the hydrated excess proton in water developed directly from ab initio molecular dynamics (AIMD) simulation data of the same system. The potential of mean force along the proton transfer reaction coordinate and radial distribution functions for the MS-RMD models are shown faithfully reproduce those of AIMD. The models are developed using an algorithm based on relative entropy minimization, thus demonstrating the ability of the method to rapidly generate accurate and highly efficient reactive MD force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗